Srisuttee, Ratakorn

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Srisuttee, Ratakorn
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ratakorn.sr@kmitl.ac.th

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    Item type:Publication,
    Determining the Optimal Parameters for Preventing Backward Falls Using a Human Movement Dataset: An Investigative Study
    (2024-01-01)
    Yoneyama, Keito R.
    ;
    Sermswan, Anawat
    ;
    Jansri, Ukkrit
    ;
    Srisuttee, Ratakorn
    Falls are a major health concern, particularly for the elderly, as they often lead to severe injuries like hip fractures. Fortunately, there are a lot of publicly available datasets that can offer valuable insights regarding the mechanics of falls and activities of daily living. This study aims to determine the optimal prevention threshold for backward falls using available datasets, thereby avoiding any fall-related injuries. The methodology employed in this study involves identifying downward trends of acceleration and angular velocity on the graph. The Pythagorean Theorem is used to calculate the resultant acceleration, while differences are computed to determine the changes in angular velocity. The results from 150 samples shows that the acceleration for the prevention threshold range is between 3.016m/s<sup>2</sup> - 4.308 m/s<sup>2</sup>and the average angular velocity is 0.522 rad/s - 0.746 rad/s which not only prevents a person from falling backward but will also be able to distinguish between activities of daily living. In conclusion, using existing dataset can offer essential knowledge into fall detection and serves as a foundation for determining the optimal fall prevention threshold.
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    Item type:Publication,
    AI Chatbot for Post-Operative Oral Surgery Information and Support
    (2025-08-07)
    Warin, Kritsasith
    ;
    Taetragoo, Unchalisa
    ;
    Trachoo, Vorapat
    ;
    Khanijoh, Chanon
    ;
    Saepong, Pechdanai
    This study presented the development of an AI chatbot specifically designed to address oral surgery-related inquiries. The chatbot, trained on a dataset of 240 questions, utilized machine learning algorithms to predict the corresponding operation for each question. The best model achieved accuracy of 0.906 in responding to questions. In conclusion, this AI chatbot has the potential to improve patient care by providing clear information to enhance post-operative outcomes.